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  3. Vrije Universiteit Amsterdam (VU)
  4.  
  5. Consumer marketing (E_EBE3_CBEH)

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Summary of all required readings + readings lecture and working group
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  • Course
  • Consumer marketing (E_EBE3_CBEH)
  • Institution
  • Vrije Universiteit Amsterdam (VU)

All articles that were extensively summarized during the lectures, workgroups and mandatory articles. Includes all relevant photos from the articles.

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Document information

  • October 22, 2023
  • 61
  • 2023/2024
  • Summary

Subjects

  • master marketing
  • consumer marketing

Written for

  • Vrije Universiteit Amsterdam (VU)
  • Business Administration: Marketing
  • Consumer marketing (E_EBE3_CBEH)
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Anik, Hauser, and Gibson (2020) - to understand consumer behavior, think like a marketplace
scientist
- Management by intuition often leads to bad judgement calls → managers should apply a
scientific approach (big data experimentation)
→ especially useful for understanding consumer behavior




- Intuition is made of heuristics that are integral to decision making → Example: availability
heuristic (I see a plain crash on the news, so there must be lots of plane crashes)
- Why experiments?
→ provide evidence, power to predict and change, results are persuasive (therefore creating
bridges between people), best way to explain human behavior
- What is an experiment?
→ an investigation that involves testing a hypothesis, manipulating an independent
variable, measuring a dependent variable, and controlling for extraneous variables
● Hypothesis → not a question, must be testable and worth testing
● Independent variable → variable that you are manipulating to test for an effect on
the dependent variable
● Dependent variable → variable that you are measuring when manipulating the
independent variable. A good dependent variable must be measurable and
measured
● Controlled variables → factors that must be kept the same between groups, in
order to create reliable results
● Test group → group that receives the manipulation of independent variable tested
● Control group → group that receives no manipulation, natural state
● Measurable result→ quantifiable, sales, clicks etc
● Measured → piece of data that your organization keeps track of (Netflix,
streaming hours)
- An experiment will only produce reliable results if adhered to scientific method, but often
fails due to missing experimental elements
→ quasi experiments, focus groups, using scientific jargon leads non legitimate findings

, - When to use experiments:
● For tactical decisions, not for strategic ones (strategic are long term visions, tactic are the
steps to get there) → strategy: cut extraneous cost, tactic: mandating double sided printing
to reduce cost)
● When experimenting with tactical decisions, make the question as specific as possible →
This is also the reason that strategic ones are impossible to test, they are too broad
→ in sum: experiments used for cause and effect, of tactical rather than strategic, only for specific
research questions, where the results are measurable and measured, and estimated to results in a net
positive results for the company

Types of experiments:
- Laboratory experiments: experiments in a well-controlled environment (lab), where people
are assigned to test or control group
→ Strengths: environment will lead to precise control of independent variables and
extraneous variables. → easy replication and identification cause and effect relationship
→ Weaknesses: the degree of control is also its weakness. Calls in the question whether the
results generalizable for the real world (ecological validity)
- Online experiments: lab experiment, but online (online survey)
→ strengths: Cheap and quick to run
→ weakness: quality of data (people might just fill things in, just to make money), also
generalizability to the real world might be questionable (validity)
- Field experiments: experiments in the field, natural or manipulated. In all field experiments,
participants engage in activity just as they would in the real world
→ strengths: natural setting leads to high ecological validity
→ weakness: might not be as good controlled, might muddy the data
- A/B testing: can be tested as lab, online, or field experiment. Two versions of an item are
compared, which are identical except for a single variable that the test group interacts with
→ strengths: simple and low cost
- Big data: not a real experiment. Collection of massive datasets, analyzed to reveal trends
or patterns. Difference to experiment → no manipulation independent variable
→ big data and experiment complement each other → big data for trends, experiment to
test the trend




How to conduct an experiment:
- Plan: identify a hypothesis relationship applicable to the business. The next picture are
intended to help during the plan stage:

, - Design: when designing the experiment you have to make sure that:
→ two or more conditions: control and test group
→ Large enough sample size
→ Random assignments: in order to mitigate confounding variables and to avoid selection
bias
→ hold things constant: the setting for the two groups must be as constant as possible
→ Attention checks: to make sure the participants actively engage

- Run: when the experiment is launched, when to stop? What to do when it looks like your
experiment is a total failure?
- When to stop?
→ predetermine the amount of results you want
→ use a time frame
- What to do when experiment looks like a failure?
→ no significant results between the groups, you should revisit your design

Analysis and interpretation
- Statistical significance → Only significant results are reliable, other results could be
random\
- Scalability → whether the results can be used in the real world
- Precision → your results must hold over time
- Sustainability → many field experiments focus on single interaction in the short term instead
of long term. By running an experiment over a long time, it might result in more sustainable
interventions
Final thoughts
To achieve experiments, the role of the manager is crucial to replace intuition with a test and learn mindset.
Intuition still important for the strategy and innovations, but tactical measures require experimentaiton

, Barasch, Zauberman, Diehl (2018). How the intention to share can undermine enjoyment:
Photo taking goals and evaluation of experiences
RQ: how might consumers’ salient intentions to share an experience in the future affect their
enjoyment of that experience in the present? → in the context of photo taking: how does making
photos with the intention to share them influence enjoyment of later experience?
Findings: intention to share photos with other is salient during the experience, it decreases
consumers’ enjoyment of the experience, relative to taking photos for the self
Why? → taking photos to share involves the prospect of being judged by others, increasing self-
presentational concern
Several factors that alter the effect enjoyment, such as individuals’ propensity to care about how they
are perceived by others and the closeness of the intended audience.
→ self presentational concern can also indirectly diminish enjoyment by reducing engagement
with the experience
Sharing experiences
Experiences are central to well-being because they are often shared with others, contributing to value
and happiness from social relationships
Sharing can happen in two ways: participating jointly or telling the experience to people who
were not there → can boost people’s sense of meaning
Article focuses on sharing photos → requires an action (taking a pic) while the experience
unfolds. Second, photos provide others with specific details of the experience that may be difficult
to communicate otherwise.
Objective article: to isolate how the goals driving photo-taking behavior affect enjoyment of an
experience, conditional on photos being taken. We compare the the effects of an intention to share
photos to another prevalent goal: the desire to preserve and protect future memories by taking actions
in the present
Hypotheses:
H1: relative to taking photos for the self, taking photos with the intention to share with others will
reduce enjoyment of the experience
H2: Relative to taking photos for the self, taking photos with the intention to share with others will
increase presentational concern
H3: Self-presentational concern will diminish enjoyment both directly and indirectly through
reduced engagement in the experience

Five studies to test the hypothesis, study 1&2 field study with correlational (1) and experimental data
(2). Study 3, 4, 5 laboratory paradigm that stimulates real life experiences

Study 1: Photo taking at a tourist attraction
Survey people who were visiting rocky-mountains and who were in line to take a picture
Method: ask the people for who they took the photo, whether they enjoyed the experience, if they
would recommend the destination
Results: goal photo → for themselves or to share
IV: goal photo
DV: enjoyment and recommendation
If the the goal of the photo is to share, enjoyment and recommendation decreases
Because the study is correlational, we cannot rule out that the causal effect is in the opposite direction
(people choose different photo goals depending on how much they enjoy the experiment)

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